KAIST Interactive Bicycle Racing Simulator" The 2nd Version with Advanced Features

Dong-Soo Kwon ~, Gi-Hun Yang*, Youngjin Park*, Sunmin Kim*, Chong-Won Lee*, Jae-Cheol Shin*,

Soonhung Han*, Jonghwan Lee*, Kwangyun Wohn*, Sehoon Kim*, Doo Yong Lee*, Kyungno Lee*, Jae-

Heon Yang*, Yun-Mook Choi*

1Korea Advanced Institute of Science and Technology, Daejon, KOREA, ]~m, onds@me.kaist.ac.kr *Korea Advanced Institute of Science and Technology, Daejon, KOREA, bicvcle@dsg.kaist.ac.kr

Abstract

This paper presents the KAIST interactive bicycle racing simulator system, which consists of a pair of bicycle simulators. The rider on the racing simulator experiences realistic sensations of motion, while being able to see the other bicycle simulator and having the audio-visual experience of riding in a velodrome or on the KAIST campus. The 2nd bicycle of the racing simulator system consists of a bicycle, a 4-DOF platform, a handlebar and a pedal resistance system to generate motion feelings; a real-time visual simulator, a HMD and beam projection system; and a 3D sound system. The system has an integrating control network with an A OIM (Area Of Interest Management) based network structure for multiple simulators.

1. Introduction

Various vehicle simulators such as automobile, bicycle, flight, tank and ship simulators have been developed and have subsequently been put into wide practical use, including in the testing of design, evaluation of environments, training for driving, entertainment applications, etc[1]. Even though many papers have been presented regarding various riding simulators, there have been relatively few studies related to two-wheeled and human-powered simulators.

The Max-Plank institute developed a bicycle simulator that consists of a visual simulator with a large truncated cone-shaped projection screen and a simple motion generation system [2]. Carnegie Mellon University also made an elementary bicycle simulator using a head mounted display (HMD) and a simple pedaling device [3]. Recently, Nanyang University developed a bicycle simulator using a 6-dof Stewart platform, an HMD and a force feedback system [4].

We also developed a bicycle simulator and studied essential issues and integration technologies in order to develop more advanced interactive simulators[5]. It has been named as the "KAIST interactive bicycle simulator". To make a more advanced racing simulator for multi-users, we have developed another KAIST

interactive bicycle simulator that has a 4-DOF platform and 3D sound. In addition, a network has been established to link the 1st version simulator and the 2nd version to do racing in the virtual world. The network is ready for a large number of simulators. In the bicycle racing simulator, the rider races against another rider on the other bicycle simulator in a velodrome or on the KAIST campus. This paper introduces advanced features of the KAIST interactive bicycle racing simulator for multi-users; a 3D sound system, a motion generation system, bicycle dynamics, handlebars and pedal resistance systems, a visual simulator, a system integration technique, and the network structure.

2 . 3 D Sound Render ing

2.1.3D sound effect

Human vision is mostly confined to the area directly toward one's front and we heavily depend on our sense of hearing to gather information in areas out of our line of vision. Thus, a virtual reality system with 3D sound effects gives a rider a much better sense of reality.

Through 3D sound effects in the virtual world created for the bicycle simulator, riders hear sounds from a simulated environment, including those of flying birds, a helicopter in the sky, people sneezing or whistling, and moving passenger cars. The racers in the virtual velodrome can hear sounds from the other racer, such as gasping in real-time because the two bicycle simulators, although at different places, mutually share information through networking. Different 3D sound systems were implemented for each bicycle simulator. In one, a multi- channel speaker system is used and in the other, a typical headphone is adopted to create the 3D sound. The two 3D sound systems are introduced in the next two sections, respectively.

2.2. Multi-channel 3D sound system

The 3D sound system for the 1st version simulator has been implemented using the eight loudspeakers. Three speakers above the simulator and five speakers in the ground were arranged. We used four stereo sound

cards for eight channels. A windows program to control the multi-channel audio system has been developed using Microsoft Visual C++ and DirectSound API. The vector base amplitude panning (VBAP) algorithm [6] is used to drive the speaker outputs for the 3D effect.

The 3D sound system needs the 3D vectors in relative coordinates between the rider and the virtual sound source. The vectors come to the audio system through UDP communication with the visual part in real time. The VBAP algorithm calculates the speaker outputs from the vector. Satisfactory performance of localization was verified experimentally.

2.3. Binaural sound system

The 3D sound system for the 2nd version simulator has been implemented using stereo headphones. A windows program to control the audio system has been developed using Microsoft Visual Basic and DirectX Audio SDK. The sound source is filtered with HRTF (head relative transfer function) [7], which is an acoustic transfer function between a sound source and the user's eardrums. The filtered sound is generated using typical headphones for the 3D effect.

We used the same data communication as that of the multi-channel 3D sound system. The viewpoint vector of the rider is obtained by the head tracker attached on the HMD(head mounted display). The 3D vector in the relative coordinates is transformed with the viewpoint vector. The headphone output is obtained with a convolution of a sound source and the HRTF corresponding to the transformed 3D vector. The satisfactory performance of sound source localization

with visual cues has been achieved through experiments.

3. Motion Generation Algorithms and System

3.1 Motion Generation Algorithms

Motion generation algorithms for the bicycle simulator were developed, which are capable of real- time bicycle dynamics simulation, washout filtering and road profile reshaping. The real-time bicycle dynamics simulation engine was developed based on a nonlinear bicycle dynamic model, accounting for tire flexibility, slip and rider's pedal, handlebars and tilting moment inputs. In order to derive the equation of motion of bicycle model, the Newton-Euler method was used. After some coordinate transformations for describing a certain bicycle geometry, four free body diagrams of front and rear wheels, frame and handlebars were taken into account. Twenty-four unknown parameters including the rear wheel position, the steering angle, the angular positions of the front and rear wheels relative to the handle fork and the frame, some internal forces and some angles for coordinate transformations can be calculated by the same number of established equations

through the method. The derived bicycle dynamics were verified through Flush 3-D graphic animation by comparing them with real bicycle motion.

The classical washout filter was programmed in accordance with the characteristics of motion systems so that it can be executed synchronous to the bicycle dynamics simulation engine. Tuning of the washout filter involves the fine adjustment of filter parameters to rider's feel of motions. The motion not covered by the motion system is created by changing the virtual rider's sight orientation so that the scene orientation projected on wall-fixed screen or head mounted display can be effectively changed. A low pass filter for reshaping the road profile data was also used to protect the bicycle dynamics solution from abnormality caused by discrete and delayed road profile data.

The motion data made by motion generation algorithm are transferred to the corresponding motion system.

Fig. 1: KAIST bicycle racing simulator

3.2 Motion System

The motion system plays an important role in providing the sensation of real motion to a simulator rider. Two kinds of motion generation systems are used for the racing bicycle simulator. One is a six degrees of freedom(DOF) Stewart platform and the other is a 4- DOF motion system. The Stewart platform, which is driven by an AC servo motor through a ball-screw, is designed with a load capability of 130kg and an actuator stroke of 10 cm. Table 1 shows the motion range of the system in the linear and rotational directions.

Table 1: Motion range of the Stewartplatform : :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

Long.(x) +0.131--0.115 Roll(cz) +9.78--9.78 Lateral(y) +0.111--0.111 Pitch(~) +11.2--9.17 Heave(z) +0.048--0.059 Yaw(7 ) +21.47--21.47

The tracking control performance of the system is up to 7Hz in frequency to simulate real bicycle motion. In

order to achieve this, a model-based control method that requires calculation of the platform dynamics within the sampling time was used [5]. For development of the optimized motion generation system, the motion characteristics of the Stewart platform were considered while the bicycle simulator was running. From the results from the experiments, for the case of linear motions, the specific force in the heave direction is much larger than that in the other directions and the low frequency longitudinal and lateral motions can be replaced by rotational motions such as the pitch and roll motions, respectively. However, for the rotational motions, all motions have relatively similar importance in terms of the sensation of motion. Therefore, a 4-DOF motion system with the heave motion and three rotational motions was proposed and designed. The motion platform is essentially made up of two parts: the 3-DOF parallel manipulator, consisting of a moving platform, a fixed base and three actuators, which utilize a DC servo motor and ball-screw system, and a turntable to generate the yaw motion. Table 2 shows the characteristics of the 3-DOF parallel manipulator.

Table 2: Performance of 3-d.o.f parallel manipulator Payload 300kgf

Actuator 180ram Stroke

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Heave(z) +8cm 50cm/s 0.6g

Roll(c~) +18 ° 50°/s 600°/s 2

Pitch(~) _+18 ° 50°/s 360°/s 2

The nonlinear kinematics and dynamics of the three d.o.f parallel manipulator with multiple closed loop chains were analyzed for tracking control of the motion platform. The motion platform showed good tracking control performance for the bicycle simulator[8].

4. Handlebar and Pedal system

The pedal resistance system and the handlebar reaction force system are haptic devices in the bicycle simulator. For the 2nd version, to obtain a more realistic feeling, reaction forces are reshaped with respect to the road conditions. The handlebar reaction force and the rolling resistance of a real bicycle are measured and several patterns are modeled. The differences of handlebar and pedal reaction forces for various road conditions are applied as background vibration in the handlebar system and rolling resistance in the pedal resistance system. As it is difficult to solve bicycle dynamics with road conditions, bicycle dynamics results without road conditions and a road condition profile are superposed and compared with the experimental results. Sampled road conditions are asphalt, grass, bricks, and soil. The road condition profile is expressed as a

function of velocity and road conditions. The 2nd version system places the focus on realizing

these features. As a structural change, only a motor is used at the

handlebars of the 2nd version, as shown in Fig. 2, instead of a motor and a MR-clutch together, as was the case for the 1st version. In spite of the advantages of the combination of the motor and the MR clutch in terms of generating passive/active reaction forces, the direct motor driven handle bar system is used for fast response, eliminating the 40msec rising time of the MR-clutch. However, as the motor is connected directly to the handlebars, a motor with larger torque capacity is used. Handlebar reaction forces are analyzed with the measured handlebar torque. Based on this data, a new model that is closer to the real dynamics than the old model is derived and applied to the 2 nd system. As shown in Fig. 4, the new model is closer to the measured torque than the previous one. Even though the same control algorithm is used, the handle bar feeling has been improved since various road conditions are well reflected by background vibration.

Fig. 2: Handlebar system

The basic structure of the pedal resistance system of the 2nd version is the same as the 1 st one, which has a

MR-brake and a motor connected in parallel. With increased transmission torque capacity of the coupling that connects the wheel, the MR-brake and the motor,

the system has increased reliability. In addition, a cover for the spinning parts is added to prevent possible

damage by the rider and to increase operation safety.

- , . - : r ..............

.... ._k

Fig. 3: Pedal resistance system

Since the pedaling resistance force for road conditions is dominantly affected by the rolling resistance between the bicycle's wheels and the road, a rolling resistance

model has been added to the dynamics simulation engine to calculate the pedal resistance force. Rolling resistance is modeled assuming it is proportional to bicycle velocity with additional variations due to different road conditions. Experimental results for rolling resistance are used to model road condition effects. Realistic pedal feeling has been improved with fine-tuning of the control gains and the addition of rolling resistance.

Torque Plot with Time History 2.5

~~ Solid line" Measured data • , , " New model data

~. xxx: Old model data

-°i /', - 1 . 5 ~

-2 0 1 2 3 4 5

Time(s)

Fig 4: Torque plot with models

5. Visual Simulator

The visual simulator creates dynamic images for the simulator, and visually expresses the virtual world in which the user travels. Visual information plays an important role in perceiving objects.

5.1. Modeling

Two different 3D models are being used for the visual simulation. One is a campus model of KAIST, and the other is a velodrome. For the campus model, geographical features and buildings are modeled separately. We modeled roads and geographical features based on a 1:5000 map of KAIST. To model buildings, we changed DXF format into 3ds format, which is then handled by MultiGen Creator TM

[10]. For the velodrome model, the curve of the track is calculated by Mathematica [9]. The curves in DXF format are re-touched by MultiGen Creator. The other parts of the velodrome are modeled by 3D Studio Max. To aid real-time simulation, unnecessary detailed information, not seen by the observer, is removed using MultiGen Creator TM. For realism, photographs were used as texture. However, more weight is given to the real-time rendering over the quality of images.

5.2. Implementation of the Visual Simulation

Our system uses the commercial product Vega TM or an application called Kitten that has been developed by KAIST [11]. With the rider's input and the geographical information

from the visual database, the bicycle dynamics can calculate the location of the bicycle. The visual simulator creates images from the calculated location. Fig. 5 shows virtual worlds created using Vega TM.

For the image creation, the visual simulator obtains the front and the rear wheel locations from the bicycle dynamics in addition to the user location. It then gives geographical information such as the contact points of the wheels with the ground, normal vectors, and the ground condition (asphalt, brick, or grass) to the bicycle dynamics. To create realistic sounds, object information such as relative position to an observer, object ID, and ground condition are sent to the acoustic system. For the multi-user system, each visual simulator communicates with a distributed server. (State exactly what "it" is here) transmits the rider's position to the server, and obtains the position of the other rider located somewhere in the distributed network. A rider can see the created images with a beam projector or an HMD (Head Mounted Display). For the HMD, we use a 3-DoF tracker to sense the orientations of the rider's head.

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Fig. 5: Image of the velodrome model from Vega ~M

5.3 Visual Simulator(Kitten)

We have developed Kitten, a general-purpose virtual reality software, the basic design of which focuses on the complexity-independence principle described above. Kitten is a Win9x/WinNT based API (Application Programming Interface). The structure of a typical virtual reality application, including the Kitten library, is depicted in Fig. 6.

Application

User Interface X-CAT

(OpenGL, GLIDE)

Fig. 6: VR system using Kitten

Kitten consists of a Renderer which performs visual and auditory rendering, and a Simulator which "runs" the

virtual world. A multiple thread structure is used to handle the complexity-independence. For rendering, if the scene complexity increases, Renderer adjusts the number of polygons by using techniques such as scene culling, LOD (Level of Detail), and texture optimization. Virtual reality applications written in Kitten - including the bicycle simulator presented in this p a p e r - are formed with the User Interface and X-CAT on top of Kitten. For our bicycle simulator, X-CAT performs collision detection, and generates the data regarding bicycle dynamics. We implemented a collision detection method by using Axis-Aligned Bounding Box (AABB) and the Ray-Triangle Intersection Algorithm.[12][13] The User Interface module receives various 3D sensor inputs from the bicycle. In addition, we allowed multiple users to join a virtual environment and compete in a race. Automatic objects are added that can travel independently in the virtual environment. However, these objects must satisfy the following property: All objects moving in a virtual environment need to locate the same positions in each client to be synchronized. As a solution, we have proposed the following method: In each client, she passes her information (position, velocity, euler angle, road type...) to the server through the network, and the server broadcasts her information, and other clients receive it from the server to display her bicycle. For automatic objects, the server regards the first access client as the master client. The master client sends object information to the server, and the server broadcasts the information, and other clients receive it from the server to display the objects. This satisfies the synchronization. A photograph of the bicycle simulator application running with automatic objects is shown in Fig. 7.

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Fig. 7: Running the bicycle simulator application with automatic objects

computer I controls the motion platform; control computer IX computes the bicycle dynamics and controls the handlebar and pedal resistance systems; control computer III displays the 3D campus models; control computer IV generates the 3D sound. It takes 0.42 ms for control computer I to communicate 32 bytes signals with control computer II through a QNX node. The term "node" or "QNX node" is a computer on the QNX network such as Ethernet and serial using native QNX messaging. It takes 0.76 ms for control computer IX to communicate 128 bytes signals with control computer III through TCP/IP protocol. These communication periods are short enough to synchronize the control systems in real time.

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Fig. 8: The input and output signals of the control computers and processes

The User Interface helps to easily select the options, such as number of riders, kinds of 3D graphic models, and driving modes, as shown in Fig. 9. The User Interface lists its own options to be selected and the status of the other bicycle simulator. The counterpart rider can be invited to play together through the User Interface. The two bicycle simulators are run together with the common graphic models.

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6. System Integration

The system integration focuses on implementation of communication and synchronization among the scenes, the motion of the platform, the reaction of the handlebar and pedal resistance systems, and the 3D sound.

As shown in Fig. 8, the bicycle simulator control system consists of four control computers: control

7. Network structure for Bicycle Simulator

We have developed a server/client library that efficiently facilitates a large number of bicycle simulators to interact with each other over the TCP/IP network. Using the client library, each simulator connects to the server, and interchanges states/event data for interaction through the server.

The server uses cell-based AOIM [14][15](Area Of Interest Management) to send data to each client. AOIM allows each client to receive data from other nearby clients, thus greatly reducing the number of network messages processed at the bicycle simulators. Thus the simulator's states data is also transferred efficiently even in the case of many participants.

The client library is placed at a visual simulator among the components of the bicycle simulator because the visual simulator uses data of opponents more often than other components and it contains all the states of the bicycle simulator. The visual simulator periodically sends its own state data to the server. Data received from the server is distributed to the Bicycle Dynamics node and Bicycle Acoustics node.

Data transmitted between clients through the server consists of the following:

• Front, rear wheel positions and normal vectors • Viewpoint position and normal vector • Direction of handlebars • Road type • Velocity

Use of the client library has minimal effect on the rendering performance of the visual simulators. When each simulator sends data 10-20 times per a second, the bicycle movements are displayed without interruption. Moreover, the bicycle actions can be expressed almost simultaneously under low network delay of the KAIST campus network.

Bicycle Simulator

Bicycle Simulator

Visual Simulator

Ne~ork Clielnt

I Mo~u'e /

/ \ Dynamics Acoustics

Bicycle Simulator

Fig. 1 O: server~clients structure

7. Conclusions

The 2nd KAIST interactive simulator is introduced with system descriptions and advanced features with 3D sound and network structure for multi-users. The 3D sound system gives the rider a much better sense of reality. More realistic motion sensations and haptic feelings are realized in the bicycle racing simulator. Two kinds of visual simulators are used, an HMD and the projection screen. Network structure for the bicycle racing simulator is realized using cell-based AOIM. The bicycle racing simulator imparts a realistic feeling to the rider, capturing motions and audio-visual effects that a racer would experience on the actual KAIST campus or

in a velodrome.

8. Acknowledgements

This work is a result of the Highly Advanced National Project(HAN Project)-"Vehicle Simulator Technology for Multiusers: Bicycle Application" supported by the Ministry of Science and Technology (MOST) and Virtual Reality Research Center(VRRC) of the Korea Science and Engineering Foundation (KOSEF).

9. References

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[3] Dan Maynes-Aminzade, "A Virtual Reality Bicycle S imul ator",http://www, cmu. edu/adm/uri/surg fe llows 98/ maynes-aminzade.html

[4] Wang Yu, Stefan Bergstrom, Lars Anderson, "A True Bicyclesimulator",http ://www.drc.ntu. edu. sg/groups/drc_ www/proj ects_vr/bicycle_simulator/index, epl

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[6] V. Pulkki, "Virtual sound source positioning using vector base amplitude panning", Journal of audio engineering of society, 45(6), pp. 456-466, 1997.

[7] Durand R. Begault, 3-D Sound for Virtual Reality and Multimedia, Academic Press, 1994

[8] Ji-Won Sung, Jae-Cheol Shin, and Chong-Won Lee, "Design and Tracking Control of 4-DOF Motion Platform for Bicycle Simulator," Proceedings of the KSNVE Autumn Annual Conference, Kanwon-do, Korea, Nov., 2001, pp.235-240 (In Korean)

[9] Chris Nadovich, "1996 Olympic Velodrome Curve D e sign",http ://library.wolfram. com/demo s/v3/OlympicV elodrome.nb

[10] Multigen-Paradigm, 1998, MultiGen Creator User's Guide

[ 11 ] Multigen-Paradigm, 1997, Vega on-line user's guide [12] Haines, Eric, "Point in Polygon Strategies," in Paul S.

Heckbert, ed. Graphics Gems IV, AP Professional, Boston, pp. 24-46, 1994.

[13] Moller, Tomas, and Ben Trumbore, "Fast, Minimum storage Ray-Triangle Intersection," journal of graphics tools, vol.2, no. 1, pp.21-28, 1997.

[14] Michael R. Macedonia, Michael J. Zyda, David R. Pratt, D. P. Brutzman and Paul T. Barham, Exploiting reality with multicast groups : a Network Architecture for Large Scale Virtual Environments, Virtual Reality Annual International Symposium, 1995. Proceedings., 1995, Page(s): 2-10

[15] Michael R. Macedonia, Michael J. Zyda, David R. Pratt, Paul T. Barham and Steven Zeswitz, NPSNET : A Network Software Architecture for Large Scale Virtual Environments, Presence, Vol. 3, No. 4, Fall 1994, pp.265-287